Summary
We're looking for someone to help coach the development and delivery of our new Data Engineering Track to graduates from less privileged backgrounds. If you have 2+ year(s) of professional experience as a Data Engineer (particularly using Python, Machine Learning and/or Cloud), have excellent communication skills and experience or interest in teaching, we'd love to hear from you.
Company
Sigma Labs' (https://www.sigmalabs.co.uk/) mission is to put graduates from less privileged backgrounds on a high performance trajectory to become future technology leaders, if they so choose. We are registered B Corp meaning we have a commitment to society as well as our shareholders and investors.
The business is founded on two beliefs:
- Exceptional talent is missed everyday: talent is equally distributed, opportunity is not. The common heuristics used to judge graduates, such as which university they attend, mean that lots of genuine talent is overlooked. We rigorously source this talent while advancing the science of assessment to ensure we find and help amazing talent. This is the first half of our mission;
- Exceptional training changes outcomes: the most effective learning practices are rarely used because the institutions that invest in the training - e.g. schools & universities – are not incentivised based upon quality of the learning. Yet Bloom’s seminal educational research proved that the right methods can change learning outcomes by 2 standard deviations (2 sigmas). This is monumental, and the focus of the second half of our mission.
We seek hardworking, curious graduates from lower income backgrounds and provide world class technical training. We then employ them for 2 years & contract them to clients who require flexible talent solutions.
The Data Engineering Coach will be helping to build an innovative Coding Academy which:
- pushes the frontiers of ‘teaching coding’ through learning excellence and constant iteration;
- uses the most engaging and effective learning methodologies: from individual & group self-directed investigative learning to war gaming, real world problems, pupil/coach reversal, etc.
- outputs excellent junior data professionals after 12 weeks (with continued development part time for 2 years).
Role & responsibilities
This is a role that would suit someone bringing experience from industry or academia and wanting to have an outsized impact on our students' outcomes. You’d be working closely with our Head of Education to develop a Data Curriculum and then take it into production by leading the teaching of it.
What?
- Creating a world class Data Engineering Curriculum that emphasises our values and approach
- Coaching students (individually & in groups) on all aspects of their journey to become a Data Engineer;
- Regularly checking in with students, answering questions & helping them overcome problems;
- Participating in code reviews, pair programming interviews and other activities;
- Running workshops and live coding demonstrations;
- In time, training other coaches and helping the students deliver real world projects.
How?
Obsessing over the learning & experience: effective, long lasting, inspiring, realistic and practical. Ultimately, we’ll have a graduate for 14 weeks full time, and then 2 years intermittently. In these 2 years, we want to give them the tools to come out on top whatever happens after this.
Why?
Our mission: delivering social mobility through world class education & execution;
Requirements
Experience with & knowledge of:
- Coding: Any widely used language for Data Engineering (Python, Scala, Java, etc). Relational databases (SQLite, PostgreSQL etc)
- Data Best Practice: Understanding how to source, clean, visualise and productionize a data set or pipeline. Basic data model, quality and profiling
- Basic knowledge of algorithms and relevant computation requirements
- e.g. OLS/GLM/regression analysis, k means. Time series analysis etc
- Experience with Cloud: Experience with a Cloud Platform (e.g. AWS, GCP, Azure) and the tools surrounding it
- e.g. HDFS, Apache Spark, Apache YARN, Airflow, Docker, Kubernetes etc
- Basic experience with Machine Learning libraries and frameworks
- e.g. Pandas, Scikit-learn, Numpy, etc
- Minimum two year professional experience as a Data Engineer
Outside of technical skills we’re also looking for
- Very strong written communication skills
- Some experience of teaching, training or coaching others.
- Good communication skills and confidence when presenting.
- A patient, empathetic & curious attitude
Nice to have:
- Advanced experience with Machine Learning and AI in production
- such as Tensorflow, Pytorch
- Experience teaching programming to adults;
- Maths and Stats: Distributions, probability, hypothesis testing,
- Interest in education best practice (mastery learning, spaced repetition, flipped classrooms, etc)
Why work at Sigma Labs?
As well as the opportunity to make a real impact on the lives of people from less advantaged backgrounds alongside a passionate team of coworkers, we offer:
- A competitive salary (£40-62k depending on experience) or day rate
- £1000 annual learning and development budget
- A flexible £50/month budget for health and wellness to go on anything from Oddbox fruit deliveries, to gyms or mental health
- Regular in-person and virtual social events
Values and Behaviours
These will develop as we grow and we want this role the help shape them in the future
- Selflessness: it’s all about the team. It means being part of something bigger. If you fall, we’ll pick you up. If you’re leading, it is to help inspire and carry others;
- Thoughtful trust: it is critical that we are able to disagree with & challenge one another, so it is also important that we are kind and know what it means to build long term trusting relationships;
- Performance in the moment: what we did last year, the universities we went to, the grades we got…aren’t that important. High performing teams care about what we’re doing right now, today. We believe the mission is worthwhile, so it matters that we win…because it is through winning that we have an impact;
- Constant improvement: we’re rigorous about defined goals, measurement & adjustment – without them, improvement is impossible. We take notes, read & practise: we’re geeks through discipline or love of the grind;
- High cadence curiosity: these can conflict, but it’s a healthy balance that drives our hard work, deep interest in people and slight obsession with the right answers and correct decisions. We have a huge challenge - it matters that we progress every day in the right direction.
